Real-Time Analytics and Emerging Data Breaches in Social Media

This article discusses the importance of real-time analytics in social media and the challenges of data breaches. It explores the impact of data breaches on businesses and provides possible solutions to mitigate the risks. The article also includes case studies of major data breaches in companies like Target, Uber, and Marriott International.

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Real-Time Analytics and it’s Emerging Data Breaches in Social Media
1.0 Abstract
Real-time analytics is the process of data analysis done as the data is being released
therefore the user can conclude faster as soon as the data gets in their system. It is important in
marketing as it is possible to monitor how business is doing and adjust accordingly as data gets
in the system instead of waiting for aggregate data. A lot of businesses use social media sites
such as face book, twitter, Instagram among others to market their goods and services. This has
been essential as it is a quick way for customers to know whether the goods and services they
want to buy are available without waiting for a long period. Some of these business social media
sites can drive customers to your online motor stores to make purchases. Social media through
real-time analytics also allows interacting with customers making them loyal as they feel
involved in the business. Real-time analytics in social media is important in a business.
However, there are some challenges faced in real-time analytic in social media; sometimes real-
time social media analytics are ignored. Another challenge is that most businesses were
established a long time ago when data was hard to get taking a long time in gathering and
analysis. Establishing real-time analytic becomes impossible due to the existing bureaucracy.
The other challenge which is the greatest of all is cyber security. In conclusion, real-time
analytics in social media is important in business growth but dangerous if not well secured.
Table of Contents
1.0 Abstract 1
2.0 Introduction 2
2.1 Big data privacy 3

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2.3 Real-time analytics on big data 4
2.4 Real-time analytic usage in social media 5
2.5 Effect of the big data breach 6
2.6 How privacy is hampered 7
2.7 Problems 8
2.8 The possible solutions 9
3.0 Literature review 10
4.0 Methodology 11
5. 0 Discussion and implications of research 12
6.0 Conclusion 13
7.0 References 14
8.0 Appendices 15
2.0 Introduction
2.1 Big data privacy
Data privacy is an important key in big data analysts. It is the responsibility of the user to
make sure those there us transparency in data usage and collection. There the research will
discuss the huge issues related to data privacy in many of the companies. There are privacy
issues related to the risks of discrimination and bias (Akter & Wamba, 2016). Some of the fake
news interferes with the privacy of the data in big companies.
2.3 Real-time analytics on big data

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Real-time analytics is the analysis of data as soon as it enters the system. It is important
as conclusions can be drawn faster as the data gets in the system. Big data analytics examines
data in large amounts to identify hidden insights. The concept of real-time data analytics has
been around for years. Big data analytics brings about speed and efficiency (Williamson, 2016).
This ability of a business to work faster gives the organization a competitive edge that was not
there before. Big companies used big data analytics and got values in the following ways; Cost a
reduction which involves big data technologies such as Hadoop store large amounts of data
(Gandomi & Haider, 2015). Faster decision making of data is analyzed immediately; it is
possible to note where to adjust your business. New products and services as you gauge your
customers' needs you can give them what they want.
2.4 Real-time analytic usage in social media
Real-time analytics is used in social media to market goods in a business. This involves
creating social media platforms for your business (Cammack, 2015). Here, you get to keep in
touch with your customers and therefore improving the business where and when need be.
Involving the customers makes them loyal to your business as they feel like part of the business.
Customers give ideas for the growth of a business by asking for the things that they need (Perera,
Liu & Jayawardena, 2015). Real-time analytics also helps know how the competitor is doing.
This is important when running a business as you know your competitors’ prices, types of goods
and services they are offering and also the comments and responses they are getting from the
customers helping adjust accordingly.
2.5 Effect of the big data breach
Data breaches have a lot of negative effects on business. For starters, most of the
businesses that incur a data breach fail with the next three years after losing the data. Businesses

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invest a lot of money and to ensure the smooth running of their social media and online sites but
once the breach occurs, all that time and money becomes worthless. It also takes a lot of time and
effort to rebuild trust among all stakeholders in business after a data breach (Mackey & Nayyar,
2017). Lack of trust among the employees, the employers and other stakeholders in a business
can lead to the failure of a business. These cyber thieves often use viruses such as Storm Worm
and WannaCry.
Figure 1: Data privacy
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2.6 How privacy is hampered
There is several privacy hampering factors on the real-time analytics data breach. The
amount of data that is stored online is growing at an unprecedented rate exceeding even the
growth of the economy by approximately four times. He suggests that we generate about 16.3

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zettabytes of data per year and by the year 2025 that will increase to 163 zettabytes (Sahay &
Ranjan, 2018). According to an article by Nick Layzel, nearly half of all the businesses in the
UK have reported at least one data breach in the last year. The risk of being targeted by
cybercriminals seems to be directly proportional to the size of the business. Large businesses are
at a higher risk of being breached with a percentage of approximately 68% (John, 2015).
2.7 Problems
Data breaches are dangerous as one can lose or compromise customers’ information. In
the infamous Equifax data breach that happened between May and July 2017, the cyber criminals
accessed personal information of around 800,000 consumers. This scares people from engaging
in businesses that involve storing large amounts of private data. Data breaches might not be
completely eradicated however; there are some ways through which the breaches could be
reduced. One of the ways is by limiting access to data. In most organizations, a lot of employees
can access the data anytime they want without necessarily having someone to monitor what they
do with the data. This makes it hard to identify the source of a data breach once it occurs since a
lot of people could have accessed it (Wedel & Kannan, 2016). The solution to this is limiting the
data accesses to a very small group with high clearance in the organization. This is good as the
CEOs or the supervisor can keep a record of the people that accessed the data and the type that
they accessed (Schwartz & Janger, 2016). The server rooms should be kept locked with a lock
that uses smart cards so that it may record the details of the person accessing the data and also
the time they accessed it. The other way of reducing data breaches is by identifying sensitive
data. This is important as the company or organization will ensure it has the right tool and
conditions to store the most important data. The sensitive data might account for less than 20%

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but when lost a company can incur a lot of losses. When the sensitive data is well protected this
will give more labor force and resources to protect the other data from breaches.
2.8 The possible solutions
Citing an example from the Cambridge Analytica scandal for Trump Campaign there was
data breach resulting in his wine. Concerning the trump campaign scandal reported by
Cambridge, analytica shown in Netflix on deep fake software which was used to manipulate the
videos to grasp the people’s minds was a major breach of the data (Sundberg, 2018). The data
interfered and the polling server could have a predicted error against his opponents in the
election (Kato, 2017). Prep-planning on data security policy is also an important way towards
protecting the data from breaching. This helps in knowing the procedure to follow at a time when
under attack by cybercriminals (Seidl, 2016). It helps react to prevent extreme losses of data
during an attack. By access management, it is easier to know which user in the organization
could have been affected by the breach. The data security policies have to be updated as
technology is always changing. It would be better if people were employed to check whether
there are updates and upgrade the policies if need be to keep them relevant.

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Figure 2: Data privacy solutions
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Sensitive data should be locked away with strong passwords. Strong passwords make it
harder for hackers to access sensitive data. It is advisable to include different characters in your
passwords to make them stronger. The character should involve alphabets, numbers, symbols
and capital letters to make it a bit more complicated for hackers (Wishart, 2019). Also, it is not
advisable to use the same passwords for different departments and serves as the hackers might
try the password they cracked to access all the other servers. Some tools can be used to change
the password from time to time and also make them strong (Lupton & Williamson, 2017).
Besides, the Security use of smartcards and biometrics is very helpful when it comes to the
protection of data, especially important and sensitive ones.
Data should be backed up regularly to avoid losses. This can be done daily or weekly
depending on the resources of the organization. The data should also be protected using antivirus

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software that should be updated regularly. This can be attained by having an IT department that
is functioning in the organization. The IT department employees should be professionals. Data
breaches have caused the change in some good businesses to bad.
3.0 Literature review
Some of the affected organizations in the world as shown in include Target Stores in
December 2013. The breach was not noticed until several weeks later. The credit and debit card
information of 110 million people information was illegally accessed. The store announced that
it was hacked through a third-party HVAC vender to and the hackers had collected over 40
million numbers of credit and debit card numbers (Winn & Wrathall, 2017). By January 2014
personal identifiable information of over 70 million people had been compromised. Both the CIO
and the CEO of the company had to resign. The company had to agree to a settlement with its
customers and was given 180 days to improve its security. Strong passwords have been put into
place in the target stores to prevent another hacking in the future. The company has ensured
limited access to crucial data. They have continued assuring their customers that their data is
safely stored.
Figure 3: data breach impact

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Source: https://newsroom.ibm.com/download/Impact+of+Data+Breaches+Felt+for+Years.jpg
Another big data breach was uber in late 2016. This impacted to the exposing of personal
information of 57 million uber users and 600,000 drivers. The uber company did not make the
breach public until a year later. The company did not handle the situation as good as their
customers expected them to as they paid the hackers a hundred thousand dollars to destroy the
data without being sure whether the hackers destroyed the data. Some of the data compromised
were the customer’s addresses and their email addresses which are very sensitive data. This
resulted in the firing of the CSO Mr (Polonkey, 2016). Sullivan as he was blamed for the breach.
The public doesn’t know for sure whether Mr. Sullivan was responsible for the breach or not.
The breach cost the company a great deal in terms of reputation and money. At the time of the
incident, the company was in talks with Softbank. Its valuation dropped from $68 billion to $48
billion but not all the drop was as a result of the breach (Ritter, Wright, Casey & Mitchell, 2015).
Since the time of the incident, Uber Company has upgraded its cyber security to ensure no
unauthorized person can access the personal information of the customers, the drivers or the
company. Uber Company has frequently assured their service users that their information is safe
(Kitchin, 2017).
Another one of the victims of this problem is Marriott International. The hack took a
period of almost for years from 2014 to 2018. Data of about 500 million people were stolen. The
breach occurred on systems that supported Starwood hotel brands. Among the information that
was stolen were guest numbers, passport numbers, travel information, credit card numbers, and
other personal information (Mergel, Rethemeyer & Isett, 2016). The company is not certain
whether the credit cards were decrypted or not. The breach was later said to have been done by
Chinese intelligence to gather information about American citizens. If this is true, then this will

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be the biggest data breach done by a nation. Adult Friend Finder also suffered a data breach in
October 2016. The breach affected more than 412.2 million accounts. Adult Friend Finder is an
online adult site where adults meet and hookup. Data collected for 20 years was breached. The
information included names, email addresses, and passwords. The passwords used to protect the
data were weak and easy to hack.
Figure 4: data breach factors
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The bank of Bangladesh was another organization affected by the big data breach which
led to a loss of $81 million in the year 2016. The hackers were suspected to be from South
Korea. The hackers breached the bank system by the use of the SWIFT network. They breached
the system in such a way that they sent the fraudulent money order transfer to the New York
branch in the United States of America central bank. Some of the money was connected to the
Casino system. This was one of the largest World Bank heist. This was a result of the data breach

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which led to a loss of large amounts of money in the bank of Bangladesh (Rao Suma & Sunitha,
2015). Some of the cash was able to be recovered but unfortunately, the amount stolen through
the casino play was unable to be recovered. There are so many incidents in the world where
many companies and organizations daily. Besides, there are incidents daily where people lose a
lot of money through hacking and breaching of data. Online banking has been a major threat to
data breaches leading to a lot of challenges. It was reported that 30% of online transactions are
affected by fraud activities (Kusumoto, 2016). Some hackers develop hacking virus which
attacks the money transacting systems leading to the redirection of the money to other accounts.
What I'm proposing on emerging data breach
I am proposing that the organization dealing with vital and sensitive data should have
data protection mechanisms. Taking an example of the banks and other organizations handling
the public information I propose the use of the anti-hackers software. The software will add some
advantages to the organization as it will protect the information from reaching the wrong
individuals. This can be done through customization and installing of the powering security
software such as Absas.net. The implementation of the security software will enhance
protection of the individual data and organizational from being breached.
4.0 Methodology
In the study of the topic under discussion, there are different methods to be used. The
methods are based on the qualitative and quantitative aspects of research. The research on other
review articles will be the most appropriate procedure for research. The reports regarding the
required information based on the requirements of the research will be well analyzed. The
researchers will follow the already analyzed reports discussing the breach of big data. The

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influence of social media on the data breach will as well be analyzed (Esposito, Castiglione, Pop
& Choo, 2017). Quantitatively, the number of breached organizations across the world will be
determined. The analysis will be based on which areas affected by the data breach issues across
the world. The cross-sectional study will be involved in this research. The surveys will be
conducted in various areas in which the data breach has been affecting. The surveys will be
conducted based on the available information regarding the emerging breach affecting the social
perspective. The rate of the social media breach will be determined by the number of the affected
groups reported in the cases before the court of law.
The survey study in this research will better method in which the primary information
regarding social media breaches. The effects of the same will be determined by the evaluation of
the effects of the same on daily activities. In this case, the dependent variables will be the
impacts of the social media breach over the organization affected. In this variable, the fact will
remain that the organization affected by the breach issues over social media will determine its
progress (Perera, Liu & Jayawardena, 2015. The reason why the impact of the social media
breach on big data is that much organization is affected beyond the recovery. It will be important
for the organization to set up the backups in case the breach happens within their organization.
This may include insurance to cover other breaches and cyber-attack (Perera, Liu &
Jayawardena, 2015). The data will be collected by noting down the incidents under which the
emerging social media breach has been affected. This will be based on world records regarding
the breach of the organization through social media.
5. 0 Discussion and implications of research

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The study needs the ethics clearance because the audience of the research needs to
understand the key issue causing the emerging social media breach. There should be a group of
people who will be involved in looking for the aim of the research as well as the methodologies
used to make sure that dignity and safety and rights will be respected in the research. Some of
the possible findings in the field include unclear methods of data protection (Zhu, 2016). The
research is expected to get the possible reasons for the data breach via social media. The chances
are expected to be a poor data security framework. The problem proposing through the research
is the poor data protection frameworks which may lead to the social media breach. Most of the
organization has no time to test the type of protection mechanisms they have regarding their data.
The solution for this is establishing a better method of data protection. The sensitive data should
be well protected by the use of the topnotch protection tools to avoid the incidents of the data
breach in many organizations.
6.0 Conclusion
The research is based on an analysis of the emerging data breaches affecting the social
media perspective. In the research, some frameworks have been put into considerations. The big
data privacy has been discussed in the research based on the requirements for the data to be kept
secret within the organization. Besides, the research has focused on real-time analytics of big
data. The real data analytics has been related to its users through social media. The research as
well focused on how data privacy has been hampered. The factors leading to data privacy
interference have been discussed in the research. The problems associated with social media data
breach have also been analyzed. In the case of the challenges facing data privacy, there are the
various organizations which have been put into consideration. The solutions for the effects of
social media data breach have been determined. Citing the example from the Cambridge

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Analytica regarding the trump campaign scandal, there so many organizations involved in the
data breach discussed in the research.

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7.0 References
Akter, S., & Wamba, S. F. (2016). Big data analytics in E-commerce: a systematic review and
agenda for future research. Electronic Markets, 26(2), 173-194.
John, V. (2015). Intelligent tutors as teachers' aides: exploring teacher needs for real-time
analytics in blended classrooms. The Seventh International Learning Analytics &
Knowledge Conference Information Systems Research, 257-266
Kusumoto, F. (2016). The application of Big Data in medicine: current implications and
future directions. Interventional Cardiac Electrophysiology review, 47(1), 51-59.
Cammack, D. W. (2015). Toward a theory of new literacies emerging from the Internet and other
information and communication technologies. Theoretical models and processes of
reading, 5(1), 1570-1613.
Esposito, C., Castiglione, A., Pop, F., & Choo, K. K. R. (2017). Challenges of connecting edge
and cloud computing: A security and forensic perspective. Peer reviewed journal of
Cloud Computing, 4(2), 13-17.
Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and
analytics. International peer reviewed journal of information management, 35(2), 137-
144.
Kato, N. (2017). A survey on network methodologies for real-time analytics of massive IoT data
and open research issues. Communications Surveys research, 19(3), 1457-1477.
Kitchin, R. (2017). The real-time city? Big data and smart urbanism. Geo Journal review, 79(1),
1-14.

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Lupton, D., & Williamson, B. (2017). The datafied child: The dataveillance of children and
implications for their rights. Peer reviewed journal of New Media & Society, 19(5), 780-
794.
Mackey, T. K., & Nayyar, G. (2017). A review of existing and emerging digital technologies to
combat the global trade in fake medicines. Expert opinion on drug safety research, 16(5),
587-602.
Mergel, I., Rethemeyer, R. K., & Isett, K. (2016). Big data in public affairs. Public
Administration Review, 76(6), 928-937.
Perera, C., Liu, C. H., & Jayawardena, S. (2015). The emerging internet of things marketplace
from an industrial perspective: Transactions research on Emerging Topics in
Computing, 3(4), 585-598.
Polonkey, S. E. (2016). The World Wide Web: a review of an emerging Internet-based
technology for the distribution of biomedical information. Peer reviewed journal of the
American Medical Informatics Association, 3(1), 1-14.
Rao, S., Suma, S. N., & Sunitha, M. (2015, May). Security solutions for big data analytics in
healthcare. International Conference on Advances in Computing and
Communication Engineering review, 3(4), 510-514.
Ritter, A., Wright, E., Casey, W., & Mitchell, T. (2015, May). Weakly supervised extraction of
computer security events from twitter. International Conference on World Wide Web
review, 4(3), 896-905.

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Sahay, B. S., & Ranjan, J. (2018). Real time business intelligence in supply chain
analytics. Research in Information Management & Computer Security, 16(1), 28-48.
Schwartz, P. M., & Janger, E. J. (2016). Notification of data security breaches research. Mich. L.
Rev., 105, 913.
Seidl, T. (2016). MOA: a real-time analytics open source framework. In Joint European
Conference on Machine Learning and Knowledge Discovery in Databases review 1 (2),
617- 620.
Sundberg, N. A. N. C. Y. (2018). Emerging issues for our hyperconnected world. The global
information technology research report, 47-56.
Wedel, M., & Kannan, P. K. (2016). Marketing analytics for data-rich environments. Review
journal of Marketing, 80(6), 97-121.
Williamson, B. (2016). Digital education governance: data visualization, predictive analytics,
and ‘real-time’policy instruments. Education Policy review, 31(2), 123-141.
Winn, J. K., & Wrathall, J. R. (2017). Who Owns the Customer-The Emerging Law of
Commercial Transactions in Electronic Customer Data. Bus. Law review., 56, 213-456
Wishart, J. (2019). Internet safety in emerging educational contexts. Computers &
Education review , 43(1-2), 193-204.
Zhu, Y. (2016). Participatory sensing-based semantic and spatial analysis of urban emergency
events using mobile social media. EURASIP Wireless Communications and
Networking review, 2016(1), 44.

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Appendices
Appendix 1: Data privacy

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Appendix: 5: Data privacy solutions

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Appendix 6: data breach impact

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Appendix 4: data breach factors